mirror of
https://github.com/BlackLight/Snort_AIPreproc.git
synced 2024-11-14 12:47:16 +01:00
710 lines
21 KiB
C
710 lines
21 KiB
C
/*
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* =====================================================================================
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*
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* Filename: correlation.c
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*
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* Description: Runs the correlation algorithm of the alerts
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*
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* Version: 0.1
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* Created: 07/09/2010 22:04:27
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* Revision: none
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* Compiler: gcc
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*
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* Author: BlackLight (http://0x00.ath.cx), <blacklight@autistici.org>
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* Licence: GNU GPL v.3
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* Company: DO WHAT YOU WANT CAUSE A PIRATE IS FREE, YOU ARE A PIRATE!
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*
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* =====================================================================================
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*/
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#include "spp_ai.h"
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#include <alloca.h>
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#include <math.h>
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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#include <unistd.h>
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#include <sys/stat.h>
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#include <time.h>
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#ifdef HAVE_LIBGVC
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#include <gvc.h>
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#endif
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#ifdef HAVE_LIBPYTHON2_6
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/*******************************************/
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/* Avoid conflicts with Snort header files */
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#ifdef _POSIX_C_SOURCE
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#undef _POSIX_C_SOURCE
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#endif
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#ifdef _XOPEN_C_SOURCE
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#undef _XOPEN_C_SOURCE
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#endif
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#ifdef _XOPEN_SOURCE
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#undef _XOPEN_SOURCE
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#endif
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/*******************************************/
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#include <Python.h>
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#endif
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/** \defgroup correlation Module for the correlation of security alerts
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* @{ */
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PRIVATE AI_snort_alert *alerts = NULL;
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PRIVATE AI_alert_correlation *correlation_table = NULL;
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PRIVATE pthread_mutex_t mutex;
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/**
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* \brief Clean up the correlation hash table
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*/
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PRIVATE void
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__AI_correlation_table_cleanup ()
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{
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AI_alert_correlation *current;
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while ( correlation_table )
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{
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current = correlation_table;
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HASH_DEL ( correlation_table, current );
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free ( current );
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}
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} /* ----- end of function __AI_correlation_table_cleanup ----- */
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/**
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* \brief Recursively write a flow of correlated alerts to a .dot file, ready for being rendered as graph
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* \param corr Correlated alerts
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* \param fp File pointer
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*/
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PRIVATE void
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__AI_correlated_alerts_to_dot ( AI_alert_correlation *corr, FILE *fp )
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{
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char src_addr1[INET_ADDRSTRLEN],
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dst_addr1[INET_ADDRSTRLEN],
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src_addr2[INET_ADDRSTRLEN],
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dst_addr2[INET_ADDRSTRLEN],
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src_port1[10],
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dst_port1[10],
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src_port2[10],
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dst_port2[10];
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if ( !corr )
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return;
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inet_ntop ( AF_INET, &(corr->key.a->ip_src_addr), src_addr1, INET_ADDRSTRLEN );
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inet_ntop ( AF_INET, &(corr->key.a->ip_dst_addr), dst_addr1, INET_ADDRSTRLEN );
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snprintf ( src_port1, sizeof ( src_port1 ), "%d", ntohs ( corr->key.a->tcp_src_port ));
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snprintf ( dst_port1, sizeof ( dst_port1 ), "%d", ntohs ( corr->key.a->tcp_dst_port ));
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inet_ntop ( AF_INET, &(corr->key.b->ip_src_addr), src_addr2, INET_ADDRSTRLEN );
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inet_ntop ( AF_INET, &(corr->key.b->ip_dst_addr), dst_addr2, INET_ADDRSTRLEN );
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snprintf ( src_port2, sizeof ( src_port2 ), "%d", ntohs ( corr->key.b->tcp_src_port ));
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snprintf ( dst_port2, sizeof ( dst_port2 ), "%d", ntohs ( corr->key.b->tcp_dst_port ));
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fprintf ( fp,
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"\t\"[%d.%d.%d] %s\\n"
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"%s:%s -> %s:%s\\n"
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"(%d alerts grouped)\" -> "
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"\"[%d.%d.%d] %s\\n"
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"%s:%s -> %s:%s\\n"
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"(%d alerts grouped)\";\n",
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corr->key.a->gid, corr->key.a->sid, corr->key.a->rev, corr->key.a->desc,
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src_addr1, src_port1, dst_addr1, dst_port1,
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corr->key.a->grouped_alerts_count,
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corr->key.b->gid, corr->key.b->sid, corr->key.b->rev, corr->key.b->desc,
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src_addr2, src_port2, dst_addr2, dst_port2,
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corr->key.b->grouped_alerts_count
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);
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} /* ----- end of function __AI_correlated_alerts_to_dot ----- */
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/**
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* \brief Recursively write the flow of correlated alerts to a .json file, ready for being rendered in the web interface
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*/
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PRIVATE void
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__AI_correlated_alerts_to_json ()
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{
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AI_snort_alert *alert_iterator = NULL;
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struct pkt_info *pkt_iterator = NULL;
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FILE *fp;
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unsigned int i = 0,
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pkt_len = 0;
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char *strtime = NULL,
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*encoded_pkt = NULL,
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json_file[1040] = { 0 },
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srcip[INET_ADDRSTRLEN] = { 0 },
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dstip[INET_ADDRSTRLEN] = { 0 },
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srcport[10] = { 0 },
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dstport[10] = { 0 };
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/* If there is no directory configured for the web interface, just exit */
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if ( strlen ( config->webserv_dir ) == 0 )
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return;
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snprintf ( json_file, sizeof ( json_file ), "%s/correlation_graph.json", config->webserv_dir );
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if ( !( fp = fopen ( json_file, "w" )))
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{
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AI_fatal_err ( "Unable to write on correlated_graph.json in htdocs directory", __FILE__, __LINE__ );
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}
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fprintf ( fp, "[\n" );
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for ( alert_iterator = alerts; alert_iterator; alert_iterator = alert_iterator->next )
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{
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strtime = ctime ( &(alert_iterator->timestamp ));
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strtime[ strlen(strtime) - 1 ] = 0;
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inet_ntop ( AF_INET, &(alert_iterator->ip_src_addr), srcip, INET_ADDRSTRLEN );
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inet_ntop ( AF_INET, &(alert_iterator->ip_dst_addr), dstip, INET_ADDRSTRLEN );
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snprintf ( srcport, sizeof ( srcport ), "%d", htons ( alert_iterator->tcp_src_port ));
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snprintf ( dstport, sizeof ( dstport ), "%d", htons ( alert_iterator->tcp_dst_port ));
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fprintf ( fp, "{\n"
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"\t\"id\": %lu,\n"
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"\t\"snortSID\": \"%u\",\n"
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"\t\"snortGID\": \"%u\",\n"
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"\t\"snortREV\": \"%u\",\n"
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"\t\"label\": \"%s\",\n"
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"\t\"date\": \"%s\",\n"
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"\t\"clusteredAlertsCount\": %u,\n"
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"\t\"from\": \"%s:%s\",\n"
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"\t\"to\": \"%s:%s\",\n"
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"\t\"latitude\": \"%f\",\n"
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"\t\"longitude\": \"%f\"",
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alert_iterator->alert_id,
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alert_iterator->sid,
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alert_iterator->gid,
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alert_iterator->rev,
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alert_iterator->desc,
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strtime,
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alert_iterator->grouped_alerts_count,
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srcip, srcport, dstip, dstport,
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alert_iterator->geocoord[0],
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alert_iterator->geocoord[1]
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);
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if ( alert_iterator->stream )
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{
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fprintf ( fp, ",\n"
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"\t\"packets\": [\n" );
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for ( pkt_iterator = alert_iterator->stream; pkt_iterator; pkt_iterator = pkt_iterator->next )
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{
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encoded_pkt = NULL;
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pkt_len = pkt_iterator->pkt->pcap_header->len + pkt_iterator->pkt->payload_size;
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if ( !( encoded_pkt = (char*) calloc ( 4*pkt_len + 1, sizeof ( char ))))
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{
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AI_fatal_err ( "Fatal dynamic memory allocation", __FILE__, __LINE__ );
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}
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base64_encode (
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(const char*) pkt_iterator->pkt->pkt_data,
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pkt_len,
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&encoded_pkt
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);
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fprintf ( fp, "\t\t\"%s\"%s\n",
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encoded_pkt, ((pkt_iterator->next) ? "," : ""));
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free ( encoded_pkt );
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encoded_pkt = NULL;
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}
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fprintf ( fp, "\t]" );
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}
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for ( i=1; i < alert_iterator->grouped_alerts_count; i++ )
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{
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if ( i == 1 )
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{
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fprintf ( fp, ",\n\t\"clusteredAlerts\": [\n" );
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}
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if ( alert_iterator->grouped_alerts )
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{
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if ( alert_iterator->grouped_alerts[i] )
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{
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strtime = ctime ( &(alert_iterator->grouped_alerts[i]->timestamp ));
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strtime[ strlen ( strtime ) - 1 ] = 0;
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inet_ntop ( AF_INET, &(alert_iterator->grouped_alerts[i]->ip_src_addr), srcip, INET_ADDRSTRLEN );
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inet_ntop ( AF_INET, &(alert_iterator->grouped_alerts[i]->ip_dst_addr), dstip, INET_ADDRSTRLEN );
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snprintf ( srcport, sizeof ( srcport ), "%d", htons ( alert_iterator->grouped_alerts[i]->tcp_src_port ));
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snprintf ( dstport, sizeof ( dstport ), "%d", htons ( alert_iterator->grouped_alerts[i]->tcp_dst_port ));
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fprintf ( fp, "\t\t{\n"
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"\t\t\t\"id\": %lu,\n"
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"\t\t\t\"label\": \"%s\",\n"
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"\t\t\t\"date\": \"%s\",\n"
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"\t\t\t\"from\": \"%s:%s\",\n"
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"\t\t\t\"to\": \"%s:%s\",\n"
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"\t\t\t\"latitude\": \"%f\",\n"
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"\t\t\t\"longitude\": \"%f\"%s",
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alert_iterator->grouped_alerts[i]->alert_id,
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alert_iterator->grouped_alerts[i]->desc,
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strtime,
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srcip, srcport, dstip, dstport,
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alert_iterator->grouped_alerts[i]->geocoord[0],
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alert_iterator->grouped_alerts[i]->geocoord[1],
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(( alert_iterator->grouped_alerts[i]->stream ) ? ",\n" : "\n" )
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);
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if ( alert_iterator->grouped_alerts[i]->stream )
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{
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fprintf ( fp, "\t\t\t\"packets\": [\n" );
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for ( pkt_iterator = alert_iterator->grouped_alerts[i]->stream; pkt_iterator; pkt_iterator = pkt_iterator->next )
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{
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if ( !pkt_iterator->pkt->ip4_header )
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{
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pkt_len = pkt_iterator->pkt->pcap_header->len +
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pkt_iterator->pkt->tcp_options_length +
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pkt_iterator->pkt->payload_size;
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} else {
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pkt_len = pkt_iterator->pkt->ip4_header->data_length;
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}
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if ( !( encoded_pkt = (char*) malloc ( 4*pkt_len + 1 )))
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{
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AI_fatal_err ( "Fatal dynamic memory allocation", __FILE__, __LINE__ );
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}
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memset ( encoded_pkt, 0, 4*pkt_len + 1 );
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base64_encode (
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(const char*) pkt_iterator->pkt->pkt_data,
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pkt_len,
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&encoded_pkt
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);
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fprintf ( fp, "\t\t\t\t\"%s\"%s\n",
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encoded_pkt, ((pkt_iterator->next) ? "," : ""));
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}
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fprintf ( fp, "\t\t\t]\n" );
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}
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fprintf ( fp,
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"\t\t}%s\n",
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(( i < alert_iterator->grouped_alerts_count - 1 ) ? "," : "" ));
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}
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}
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if ( i == alert_iterator->grouped_alerts_count - 1 )
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{
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fprintf ( fp, "\t]" );
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}
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}
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for ( i=0; i < alert_iterator->n_derived_alerts; i++ )
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{
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if ( i == 0 )
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{
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fprintf ( fp, ",\n\t\"connectedTo\": [\n" );
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}
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fprintf ( fp, "\t\t{ \"id\": %lu }%s\n",
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alert_iterator->derived_alerts[i]->alert_id,
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((i < alert_iterator->n_derived_alerts - 1) ? "," : ""));
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if ( i == alert_iterator->n_derived_alerts - 1 )
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{
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fprintf ( fp, "\t]" );
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}
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}
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fprintf ( fp, "\n}%s\n",
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(alert_iterator->next ? "," : ""));
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}
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fprintf ( fp, "]\n" );
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fclose ( fp );
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chmod ( json_file, 0644 );
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} /* ----- end of function __AI_correlated_alerts_to_json ----- */
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/**
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* \brief Thread for correlating clustered alerts
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*/
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void*
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AI_alert_correlation_thread ( void *arg )
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{
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int i;
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struct stat st;
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char corr_dot_file[4096] = { 0 };
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#ifdef HAVE_LIBGVC
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char corr_ps_file [4096] = { 0 };
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#endif
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double avg_correlation = 0.0,
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std_deviation = 0.0,
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corr_threshold = 0.0,
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kb_correlation = 0.0,
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bayesian_correlation = 0.0,
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neural_correlation = 0.0;
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size_t n_correlations = 0,
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n_corr_functions = 0,
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n_corr_weights = 0;
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FILE *fp = NULL;
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AI_alert_correlation_key corr_key;
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AI_alert_correlation *corr = NULL;
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AI_alert_type_pair_key pair_key;
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AI_alert_type_pair *pair = NULL,
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*unpair = NULL;
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AI_snort_alert *alert_iterator = NULL,
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*alert_iterator2 = NULL;
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pthread_t manual_corr_thread;
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#ifdef HAVE_LIBGVC
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char corr_png_file[4096] = { 0 };
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GVC_t *gvc = NULL;
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graph_t *g = NULL;
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#endif
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double (**corr_functions)( const AI_snort_alert*, const AI_snort_alert* ) = NULL;
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double (**corr_weights)() = NULL;
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#ifdef HAVE_LIBPYTHON2_6
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PyAlert *pyA = NULL,
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*pyB = NULL;
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PyObject *pArgs = NULL,
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*pRet = NULL;
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PyObject **py_corr_functions = NULL;
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PyObject **py_weight_functions = NULL;
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size_t n_py_corr_functions = 0;
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size_t n_py_weight_functions = 0;
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double py_value = 0.0,
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py_weight = 0.0;
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#endif
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corr_functions = AI_get_corr_functions ( &n_corr_functions );
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corr_weights = AI_get_corr_weights ( &n_corr_weights );
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py_corr_functions = AI_get_py_functions ( &n_py_corr_functions );
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py_weight_functions = AI_get_py_weights ( &n_py_weight_functions );
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pthread_mutex_init ( &mutex, NULL );
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/* Start the thread for parsing manual correlations from XML */
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if ( pthread_create ( &manual_corr_thread, NULL, AI_manual_correlations_parsing_thread, NULL ) != 0 )
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{
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AI_fatal_err ( "Failed to create the manual correlations parsing thread", __FILE__, __LINE__ );
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}
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while ( 1 )
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{
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sleep ( config->correlationGraphInterval );
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if ( stat ( config->corr_rules_dir, &st ) < 0 )
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{
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_dpd.errMsg ( "AIPreproc: Correlation rules directory '%s' not found, the correlation thread won't be active\n",
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config->corr_rules_dir );
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pthread_exit (( void* ) 0 );
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return ( void* ) 0;
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}
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/* Set the lock flag to true, and keep it this way until I've done with correlating alerts */
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pthread_mutex_lock ( &mutex );
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if ( alerts )
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{
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AI_free_alerts ( alerts );
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alerts = NULL;
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}
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if ( !( alerts = AI_get_clustered_alerts() ))
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{
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pthread_mutex_unlock ( &mutex );
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continue;
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}
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if ( config->use_knowledge_base_correlation_index != 0 )
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{
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AI_kb_index_init ( alerts );
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}
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__AI_correlation_table_cleanup();
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correlation_table = NULL;
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/* Fill the table of correlated alerts */
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for ( alert_iterator = alerts; alert_iterator; alert_iterator = alert_iterator->next )
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{
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for ( alert_iterator2 = alerts; alert_iterator2; alert_iterator2 = alert_iterator2->next )
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{
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if ( alert_iterator != alert_iterator2 && ! (
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alert_iterator->gid == alert_iterator2->gid &&
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alert_iterator->sid == alert_iterator2->sid &&
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alert_iterator->rev == alert_iterator2->rev ))
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{
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if ( !( corr = ( AI_alert_correlation* ) malloc ( sizeof ( AI_alert_correlation ))))
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AI_fatal_err ( "Fatal dynamic memory allocation error", __FILE__, __LINE__ );
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corr_key.a = alert_iterator;
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corr_key.b = alert_iterator2;
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corr->key = corr_key;
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corr->correlation = 0.0;
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n_correlations = 0;
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kb_correlation = AI_kb_correlation_coefficient ( corr_key.a, corr_key.b );
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bayesian_correlation = AI_alert_bayesian_correlation ( corr_key.a, corr_key.b );
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neural_correlation = AI_alert_neural_som_correlation ( corr_key.a, corr_key.b );
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/* Use the correlation indexes for which we have a value */
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if ( bayesian_correlation != 0.0 && config->bayesianCorrelationInterval != 0 )
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{
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corr->correlation += AI_bayesian_correlation_weight() * bayesian_correlation;
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n_correlations++;
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}
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if ( kb_correlation != 0.0 && config->use_knowledge_base_correlation_index )
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{
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corr->correlation += kb_correlation;
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n_correlations++;
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}
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if ( neural_correlation != 0.0 && config->neuralNetworkTrainingInterval != 0 )
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{
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corr->correlation += AI_neural_correlation_weight() * neural_correlation;
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n_correlations++;
|
|
}
|
|
|
|
/* Get the correlation indexes from extra correlation modules */
|
|
if (( corr_functions ))
|
|
{
|
|
for ( i=0; i < n_corr_functions; i++ )
|
|
{
|
|
if ( corr_weights[i]() != 0.0 )
|
|
{
|
|
corr->correlation += corr_weights[i]() * corr_functions[i] ( corr_key.a, corr_key.b );
|
|
n_correlations++;
|
|
}
|
|
}
|
|
}
|
|
|
|
#ifdef HAVE_LIBPYTHON2_6
|
|
if (( py_corr_functions ))
|
|
{
|
|
pyA = AI_alert_to_pyalert ( corr_key.a );
|
|
pyB = AI_alert_to_pyalert ( corr_key.b );
|
|
|
|
if ( pyA && pyB )
|
|
{
|
|
for ( i=0; i < n_py_corr_functions; i++ )
|
|
{
|
|
if ( !( pArgs = Py_BuildValue ( "(OO)", pyA, pyB )))
|
|
{
|
|
PyErr_Print();
|
|
AI_fatal_err ( "Could not initialize the Python arguments for the call", __FILE__, __LINE__ );
|
|
}
|
|
|
|
if ( !( pRet = PyEval_CallObject ( py_corr_functions[i], pArgs )))
|
|
{
|
|
PyErr_Print();
|
|
AI_fatal_err ( "Could not call the correlation function from the Python module", __FILE__, __LINE__ );
|
|
}
|
|
|
|
if ( !( PyArg_Parse ( pRet, "d", &py_value )))
|
|
{
|
|
PyErr_Print();
|
|
AI_fatal_err ( "Could not parse the correlation value out of the Python correlation function", __FILE__, __LINE__ );
|
|
}
|
|
|
|
Py_DECREF ( pRet );
|
|
Py_DECREF ( pArgs );
|
|
|
|
if ( !( pRet = PyEval_CallObject ( py_weight_functions[i], (PyObject*) NULL )))
|
|
{
|
|
PyErr_Print();
|
|
AI_fatal_err ( "Could not call the correlation function from the Python module", __FILE__, __LINE__ );
|
|
}
|
|
|
|
if ( !( PyArg_Parse ( pRet, "d", &py_weight )))
|
|
{
|
|
PyErr_Print();
|
|
AI_fatal_err ( "Could not parse the correlation weight out of the Python correlation function", __FILE__, __LINE__ );
|
|
}
|
|
|
|
Py_DECREF ( pRet );
|
|
|
|
if ( py_weight != 0.0 )
|
|
{
|
|
corr->correlation += py_weight * py_value;
|
|
n_correlations++;
|
|
}
|
|
}
|
|
|
|
free ( pyA ); free ( pyB );
|
|
pyA = NULL; pyB = NULL;
|
|
}
|
|
}
|
|
#endif
|
|
|
|
if ( n_correlations != 0 )
|
|
{
|
|
corr->correlation /= (double) n_correlations;
|
|
}
|
|
|
|
HASH_ADD ( hh, correlation_table, key, sizeof ( AI_alert_correlation_key ), corr );
|
|
}
|
|
}
|
|
}
|
|
|
|
if ( HASH_COUNT ( correlation_table ) > 0 )
|
|
{
|
|
avg_correlation = 0.0;
|
|
std_deviation = 0.0;
|
|
|
|
/* Compute the average correlation coefficient */
|
|
for ( corr = correlation_table; corr; corr = ( AI_alert_correlation* ) corr->hh.next )
|
|
{
|
|
avg_correlation += corr->correlation;
|
|
}
|
|
|
|
avg_correlation /= (double) HASH_COUNT ( correlation_table );
|
|
|
|
/* Compute the standard deviation */
|
|
for ( corr = correlation_table; corr; corr = ( AI_alert_correlation* ) corr->hh.next )
|
|
{
|
|
std_deviation += ( corr->correlation - avg_correlation ) * ( corr->correlation - avg_correlation );
|
|
}
|
|
|
|
std_deviation = sqrt ( std_deviation / (double) HASH_COUNT ( correlation_table ));
|
|
corr_threshold = avg_correlation + ( config->correlationThresholdCoefficient * std_deviation );
|
|
snprintf ( corr_dot_file, sizeof ( corr_dot_file ), "%s/correlated_alerts.dot", config->corr_alerts_dir );
|
|
|
|
if ( stat ( config->corr_alerts_dir, &st ) < 0 )
|
|
{
|
|
if ( mkdir ( config->corr_alerts_dir, 0755 ) < 0 )
|
|
{
|
|
AI_fatal_err ( "Unable to create directory the correlated alerts directory", __FILE__, __LINE__ );
|
|
}
|
|
} else if ( !S_ISDIR ( st.st_mode )) {
|
|
AI_fatal_err ( "The specified directory for correlated alerts is not a directory", __FILE__, __LINE__ );
|
|
}
|
|
|
|
if ( !( fp = fopen ( corr_dot_file, "w" )))
|
|
AI_fatal_err ( "Could not write on the correlated alerts .dot file", __FILE__, __LINE__ );
|
|
fprintf ( fp, "digraph G {\n" );
|
|
|
|
/* Find correlated alerts */
|
|
for ( corr = correlation_table; corr; corr = ( AI_alert_correlation* ) corr->hh.next )
|
|
{
|
|
pair_key.from_sid = corr->key.a->sid;
|
|
pair_key.from_gid = corr->key.a->gid;
|
|
pair_key.from_rev = corr->key.a->rev;
|
|
pair_key.to_sid = corr->key.b->sid;
|
|
pair_key.to_gid = corr->key.b->gid;
|
|
pair_key.to_rev = corr->key.b->rev;
|
|
|
|
HASH_FIND ( hh, manual_correlations, &pair_key, sizeof ( pair_key ), pair );
|
|
HASH_FIND ( hh, manual_uncorrelations, &pair_key, sizeof ( pair_key ), unpair );
|
|
|
|
/* Yes, BlackLight wrote this line of code in a pair of minutes and immediately
|
|
* compiled it without a single error */
|
|
if ( !unpair && ( pair || (
|
|
corr->correlation >= corr_threshold &&
|
|
corr_threshold != 0.0 &&
|
|
corr->key.a->timestamp <= corr->key.b->timestamp && ! (
|
|
corr->key.a->gid == corr->key.b->gid &&
|
|
corr->key.a->sid == corr->key.b->sid &&
|
|
corr->key.a->rev == corr->key.b->rev ) && (
|
|
corr->key.a->ip_src_addr == corr->key.b->ip_src_addr || (
|
|
(corr->key.a->h_node[src_addr] && corr->key.b->h_node[src_addr]) ?
|
|
( corr->key.a->h_node[src_addr]->max_val == corr->key.b->h_node[src_addr]->max_val &&
|
|
corr->key.a->h_node[src_addr]->min_val == corr->key.b->h_node[src_addr]->min_val ) : 0
|
|
)) && (
|
|
corr->key.a->ip_dst_addr == corr->key.b->ip_dst_addr || (
|
|
(corr->key.a->h_node[dst_addr] && corr->key.b->h_node[dst_addr]) ?
|
|
( corr->key.a->h_node[dst_addr]->max_val == corr->key.b->h_node[dst_addr]->max_val &&
|
|
corr->key.a->h_node[dst_addr]->min_val == corr->key.b->h_node[dst_addr]->min_val ) : 0
|
|
))
|
|
)
|
|
)
|
|
) {
|
|
if ( !( corr->key.a->derived_alerts = ( AI_snort_alert** ) realloc ( corr->key.a->derived_alerts,
|
|
(++corr->key.a->n_derived_alerts) * sizeof ( AI_snort_alert* ))))
|
|
AI_fatal_err ( "Fatal dynamic memory allocation error", __FILE__, __LINE__ );
|
|
|
|
if ( !( corr->key.b->parent_alerts = ( AI_snort_alert** ) realloc ( corr->key.b->parent_alerts,
|
|
(++corr->key.b->n_parent_alerts) * sizeof ( AI_snort_alert* ))))
|
|
AI_fatal_err ( "Fatal dynamic memory allocation error", __FILE__, __LINE__ );
|
|
|
|
corr->key.a->derived_alerts[ corr->key.a->n_derived_alerts - 1 ] = corr->key.b;
|
|
corr->key.b->parent_alerts [ corr->key.b->n_parent_alerts - 1 ] = corr->key.a;
|
|
__AI_correlated_alerts_to_dot ( corr, fp );
|
|
|
|
if ( config->outdbtype != outdb_none )
|
|
{
|
|
AI_store_correlation_to_db ( corr );
|
|
}
|
|
}
|
|
}
|
|
|
|
fprintf ( fp, "}\n" );
|
|
fclose ( fp );
|
|
|
|
#ifdef HAVE_LIBGVC
|
|
snprintf ( corr_png_file, sizeof ( corr_png_file ), "%s/correlated_alerts.png", config->corr_alerts_dir );
|
|
snprintf ( corr_ps_file , sizeof ( corr_ps_file ), "%s/correlated_alerts.ps" , config->corr_alerts_dir );
|
|
|
|
if ( !( gvc = gvContext() ))
|
|
continue;
|
|
|
|
if ( !( fp = fopen ( corr_dot_file, "r" )))
|
|
continue;
|
|
|
|
if ( !( g = agread ( fp )))
|
|
continue;
|
|
|
|
gvLayout ( gvc, g, "dot" );
|
|
gvRenderFilename ( gvc, g, "png", corr_png_file );
|
|
gvRenderFilename ( gvc, g, "ps" , corr_ps_file );
|
|
|
|
gvFreeLayout ( gvc, g );
|
|
agclose ( g );
|
|
fclose ( fp );
|
|
#endif
|
|
|
|
/* If no database output is defined, then the alerts have no alert_id, so we cannot use the
|
|
* web interface for correlating them, as they have no unique identifier */
|
|
if ( config->outdbtype != outdb_none )
|
|
{
|
|
if ( strlen ( config->webserv_dir ) != 0 )
|
|
{
|
|
__AI_correlated_alerts_to_json ();
|
|
}
|
|
}
|
|
}
|
|
|
|
pthread_mutex_unlock ( &mutex );
|
|
}
|
|
|
|
pthread_exit (( void* ) 0 );
|
|
return (void*) 0;
|
|
} /* ----- end of function AI_alert_correlation_thread ----- */
|
|
|
|
/** @} */
|
|
|